Role Summary



We are seeking a highly skilled Data Engineer with strong expertise in Databricks, Apache Spark, and Scala to design, develop, and optimize large-scale data processing solutions. The ideal candidate will have hands-on experience building distributed data pipelines, implementing scalable ETL frameworks, and delivering cloud-native data solutions on Azure.



Key Responsibilities



Design, develop, and maintain scalable data pipelines using Databricks, Apache Spark, and Scala.

Build ingestion, transformation, and validation frameworks for high-volume data processing.

Develop and optimize Spark jobs for performance, scalability, and reliability.

Implement and manage Databricks workflows, job orchestration, and scheduling.

Troubleshoot production issues, performance bottlenecks, and pipeline failures.

Optimize cluster utilization, Spark execution plans, and data processing efficiency.

Work with cross-functional teams to design data architectures and integration solutions.

Implement best practices for coding, testing, CI/CD, and deployment.

Support production environments and participate in incident resolution and root cause analysis.

Collaborate in Agile teams to deliver high-quality data products.

Required Skills



Strong hands-on experience in:

Databricks

Apache Spark

Scala

Spark SQL

PySpark

Experience in:

Distributed data processing frameworks

ETL/ELT pipeline development

Data modeling and data warehousing concepts

Performance tuning and optimization of Spark applications

Cloud experience:

Microsoft Azure

Azure Data Lake Storage (ADLS)

Azure Data Factory (ADF)

Strong SQL development and query optimization skills.

Experience with source control systems such as Git/GitHub.

Strong analytical and debugging skills.

Preferred Skills



Delta Lake

Unity Catalog

CI/CD pipelines (Azure DevOps, Harness)

Snowflake

Data Quality and Validation Frameworks

Financial Services / Reference Data domain knowledge

Experience with AI-assisted development tools such as GitHub Copilot

Education & Experience



Bachelor's or Master's degree in Computer Science, Engineering, or related field.

10+ years of experience in Data Engineering.

6+ years of hands-on Databricks and Spark development experience.

Strong experience developing production-grade Scala applications.

Nice-to-Have



Databricks Certification

Azure Certification

Experience with Real-Time Streaming (Kafka, Spark Structured Streaming)

Exposure to Lakehouse architecture patterns




About State Street



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We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you'll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.



As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.



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